Head of Clinician Science

Abridge
SF OfficePosted 9 March 2026

Job Description

Head of Clinician Science ABOUT ABRIDGE Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose-built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients. Our enterprise-grade technology transforms patient-clinician conversations into structured clinical notes in real-time, with deep EMR integrations. Powered by Linked Evidence and our purpose-built, auditable AI, we are the only company that maps AI-generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems. We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh. THE ROLE ABRIDGE'S CLINICAL CREDIBILITY IS BUILT ON ENSURING OUR AI OUTPUTS ARE CLINICALLY MEANINGFUL, CONTEXTUALLY APPROPRIATE, AND TRUSTWORTHY TO PHYSICIANS ACROSS SPECIALTIES AND WORKFLOWS. THE CLINICIAN SCIENCE TEAM SITS AT THE HEART OF THIS MISSION, SERVING AS THE ESSENTIAL BRIDGE BETWEEN CUTTING-EDGE AI AND THE COMPLEX REALITIES OF MEDICAL PRACTICE. We are hiring a Head of Clinician Science to lead and grow our team of clinician scientists embedded across R&D product teams. You will ensure that clinical expertise shapes product direction from day one, that AI outputs reflect real-world clinical workflows and medical best practices, and that our quality standards are grounded in what actually matters to practicing physicians. This role reports to the VP of Product and works in close partnership with ML Science, Product Management, Design, and our Commercial clinical teams. WHAT YOU’LL DO - Lead and grow the Clinician Science team. Recruit, develop, and manage a team of clinician scientists with diverse specialty expertise. Foster a culture of clinical rigor, intellectual curiosity, and cross-functional collaboration. - Ensure clinical excellence across product development. Partner with product teams to embed clinical expertise into feature discovery, design, and validation. Translate clinical workflows and best practices into actionable product requirements. - Define and uphold clinical quality standards. Establish frameworks for what "clinically meaningful" means across specialties, note types, and workflows. Guide the team in evaluating note quality, prompt iterations, and model outputs through LFD sessions and systematic assessments. - Build scalable clinical evaluation systems. Partner with ML Science to develop LLM judges, annotation frameworks, and evaluation pipelines that scale clinical expertise. Ensure evaluation methodologies reflect real-world clinical judgment, not just technical metrics. - Bridge clinical and technical domains. Serve as a translator between clinical reality and ML/engineering capabilities. Help engineers and ML scientists understand clinical nuance; help clinicians understand technical constraints and opportunities. - Close the feedback loop with Commercial. Partner with Clinical Success and Solutions Consulting to surface real-world usage insights, customer feedback, and quality issues. Ensure product development stays grounded in how clinicians actually use Abridge. - Represent clinical perspective in Builder strategy. Participate in roadmap planning, feature prioritization, and cross-pod alignment discussions. Be the voice of clinical credibility in product decisions. WHAT YOU’LL BRING - Active clinical background. MD, DO, NP, PA, or equivalent clinical degree with 3+ years of clinical practice experience. Board certification preferred. You understand the daily realities of documentation ... (truncated, view full listing at source)
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